nfcompose VS retake

I have implemented this for our tool NF Compose that allows us to build REST APIs without writing a single line of code [0]. I didn't go the route of triggers because we generate database tables automatically and we used to have a crazy versioning scheme that was inspired by data vault and anchor modelling where we stored every change on every attribute as a new record.

Sounded cool, but in practice it was really slow. The techniques that are usually employed by Data Vault to fix this issue seemed too complex. Over time we moved to an implementation that handles the historization dynamically at runtime by generating SQL queries ourselves [1]. On a sidenote: Generating SQL in python sounds dangerous, but we spent a lot of time on making it secure. We even have a linter that checks that everything is escaped properly whenever we are in dev mode [2]

[0] https://github.com/neuroforgede/nfcompose/

As part of our services we also provide support for building integrations between (our) systems and external systems. As we didn't want to keep building the same REST APIs every time, we set out to build a standardized data integratin platform that allows for a quick way to generate user specified REST API definitions via a REST API. This has become NF Compose (https://github.com/neuroforgede/nfcompose).

https://github.com/getretake/retake/pull/198 is a refreshing change given the recent rug pulls, so thank you for that

We found it difficult to do well with standard vector databases and so we ended up making a nice open-source package to layer semantic search on top of Postgres with just a few lines of code. It supports Python backends right now, always stays in sync with Postgres via Kafka, doubles as a vector store, and can be deployed anywhere.